Anjali Diwan

This book introduces the revolutionary use of AI in the field of cervical cancer detection. The book explores how advanced computer algorithms can analyze medical images and patient data to enhance early detection and accurate diagnosis of cervical cancer. The book starts by providing a comprehensive overview of cervical cancer, its risk factors, and the importance of early detection. It then delves into the fundamental concepts of artificial intelligence and its application in healthcare. Readers will gain a deeper understanding of how AI algorithms can "see" patterns in cervical cells and tissue, enabling the detection of abnormal cells and precancerous changes that may indicate the presence of cervical cancer. Drawing on the latest research and real-world case studies, the book showcases the various AI techniques used for cervical cancer screening, including the analysis of Pap smear and liquid-based cytology images. This book is an essential read for healthcare professionals, researchers, policymakers, and anyone interested in the intersection of AI and healthcare.

This book covers the basic principles of wireless communication while delving into the fundamentals of machine learning, including supervised and unsupervised learning, deep learning, and reinforcement learning. The authors provide real-world examples and case studies to illustrate the use of machine learning in wireless communication applications such as channel estimation, mobility prediction, resource allocation, and beamforming. This book is an essential resource for researchers, engineers, and students interested in understanding and applying machine learning techniques in the context of wireless communication systems.